tbuckley/cabot-search huggingface dataset:
Abstract 488: New therapeutic strategies suppressing NAD+ and ATP production in cancer metabolism specific to 3D cultured ovarian cancer cells
Authors: Kei Kudo, Brittney S. Harrington, Franklin Ning, Rahul Kamdar, Yusuke Shibuya, Soumya Korrapati, Maria Fergusson, Calen Kucera, Fantini Massimo, Christina M. Annunziata
Journal: Cancer Research (2023)

Abstract Ovarian cancer is the gynecological cancer with the highest mortality rate. As resistance to treatment is acquired and many patients relapse, new treatment strategies are needed. A model that strongly reflects the features of recurrent ovarian cancer in the peritoneal cavity is the "cancer stem cells (CSCs)," which are enriched when cells are cultured in three dimensions (3D) on low-attachment plates. The unique metabolic system of the "3D CSCs" is the subject of a novel therapeutic approach. Here, we show that ovarian cancer 3D CSCs have strong NAD+ production capacity, which is particularly dependent on nicotinamide phosphoribosyl transferase (NAMPT), known as the rate-limiting enzyme in the salvage pathway of NAD+ production. We found that NAMPT inhibition blocks NADPH and ATP production as well as NAD+, and subsequently suppresses the synthesis capacity of proteins, fat droplets, and cholesterol in the 3D ovarian cancer cells. In addition, we found that the combination of NAMPT inhibitor and the ALDH inhibitor disulfiram had a pronounced synergistic effect. This synergy inhibits oxidative phosphorylation and ALDH activity and promotes reactive oxygen species and apoptosis via caspase 3/7 cleavage, which leads to death of the 3D cultured cells. Our results demonstrate that high NAMPT expression in ovarian cancer is likely to be a strong poor prognostic factor and that the combination of a NAMPT inhibitor and disulfiram could be a new treatment option to treat or prevent recurrent ovarian cancer. Our novel findings focus on NAMPT addiction as a property of ovarian cancer 3D CSCs, and strongly suggest the combined inhibition of NAMPT and ALDH as a potential therapeutic strategy. Citation Format: Kei Kudo, Brittney S. Harrington, Franklin Ning, Rahul Kamdar, Yusuke Shibuya, Soumya Korrapati, Maria Fergusson, Calen Kucera, Fantini Massimo, Christina M. Annunziata. New therapeutic strategies suppressing NAD+ and ATP production in cancer metabolism specific to 3D cultured ovarian cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 488.
Abstract 2089: Vanishing deviance problem in high-dimensional penalized Cox regression
Authors: Sijie Yao, Tingyi Li, Biwei Cao, Xuefeng Wang
Journal: Cancer Research (2023)

Abstract Penalized regression models, such as LASSO and elastic net, have been well-established for high-dimensional variable sections. For the analysis of censored survival outcomes, the penalized Cox regression model has been widely used. The parameter tuning in the penalized regression is often implemented based on the cross-validation (CV) via the “one standard error rule” (1se rule), resulting in a more parsimonious model. However, in a high-dimensional Cox regression model, a common observation is that the CV plot for tuning parameters against partial-likelihood deviance is often not U-shaped but L-shaped. In this case, the model selection will fail with either the “1se” or the“min” rule. We observed that this phenomenon is quite universal in the setting of high-dimensional prognostic biomarker selection, in which the standard CV steps often result in no or very few features included in the final model. We refer to this phenomenon as the “vanishing deviance” (VD) problem. In this study, we investigated this problem in more depth and demonstrated the issue and potential solution using real data from pan-cancer analysis of prognostic lncRNA biomarkers. To discover the cause behind the VD problem, we conducted an extensive set of simulations by varying sample sizes, feature dimensions, censoring rates, number of true biomarkers, and significance levels of true signals.Our results indicated that the main cause of the VD problem can be related to the limited sample size in the cancer omics dataset and a large number of true (or highly associated) biomarkers or signals underlying. To this end, we propose computational solutions that can alleviate the problem and we implemented them in the R package called CoxHive. We verified the performance of our solution based on both simulation studies and the analyses of the pan-cancer gene expression data. This software tool will greatly facilitate biomarker selection (including genomic and imaging biomarkers) in the high-dimensional setting. Citation Format: Sijie Yao, Tingyi Li, Biwei Cao, Xuefeng Wang. Vanishing deviance problem in high-dimensional penalized Cox regression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2089.
Abstract 1670: Sabizabulin shows anti-cancer efficacy in HER2+ breast cancer and novel sabizabulin derivatives overcome paclitaxel-resistance in triple negative breast cancer
Authors: Kelli L. Hartman, Raisa I. Krutilina, Damilola Oluwalana, Deanna N. Parke, Hao Chen, Duane D. Miller, Wei Li, Tiffany N. Seagroves
Journal: Cancer Research (2023)

Abstract Of the four breast cancer molecular subtypes, the HER2 overexpressing subtype (HER2+) accounts for 15% of all breast cancer cases. Preferred frontline treatment relies on anti-HER2 therapies, such as trastuzumab and pertuzumab, combined with microtubule inhibitors, such as taxanes. However, the clinical efficacy of taxanes is limited by development of chemoresistance and hematological and neurotoxicities. Other agents that target tubulin, such as colchicine-binding site inhibitors (CBSIs) are a class of promising alternatives to taxane therapy due to their ability to overcome P-gp-mediated taxane resistance. Sabizabulin (formerly known as VERU-111) is a potent CBSI that is orally bioavailable, overcomes paclitaxel resistance, and inhibits tumor growth and distant metastases in triple negative breast cancer (TNBC). Here, we demonstrate sabizabulin’s anti-cancer efficacy in HER2+ breast cancer. We report that sabizabulin inhibits proliferation of HER2+ breast cancer, maintains a low nanomolar IC50 value, inhibits colony formation, and causes apoptosis in HER2+ breast cancer cell lines. Sabizabulin inhibits the primary tumor growth in an orthotopic HER2+ in vivo model, BT474, and in a patient-derived xenograft model, HCI-12. While sabizabulin shows promising results for treatment in HER2+ breast cancer, we further optimized the structure of sabizabulin to create a new class of anti-cancer molecules: 40a, CH-2-77, and 60c. Based on in vitro data, 60c showed higher potency in HER2+ breast cancer cell lines and was chosen as the lead compound to further study in a paclitaxel-resistant triple negative breast cancer in vivo study where it was able to effectively inhibit primary tumor growth compared to the vehicle group. Citation Format: Kelli L. Hartman, Raisa I. Krutilina, Damilola Oluwalana, Deanna N. Parke, Hao Chen, Duane D. Miller, Wei Li, Tiffany N. Seagroves. Sabizabulin shows anti-cancer efficacy in HER2+ breast cancer and novel sabizabulin derivatives overcome paclitaxel-resistance in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1670.
Abstract 6340: Preclinical development of a monoclonal antibody targeting CD24 as cancer immunotherapy
Authors: Wenzhi Tian, Song Li, Dianze Chen, Dandan Liu, Huiqin Guo, Chunmei Yang, Li Zhang, Wei Zhang, Xiaoping Tu, Liang Peng, Gui Zhao, Ruliang Zhang, Fan Zhang, Frank X. Gan
Journal: Cancer Research (2023)

Abstract CD24 is a novel immune checkpoint that suppresses activation of macrophages, natural killer (NK) cells, T cells and B cells by binding to inhibitory receptor Siglec-10. CD24 is highly expressed on cancers of genitourinary (GU) and gastrointestinal (GI) systems, breast, and lung. High expression of CD24 is also known to be associated with poor prognosis for many types of cancers including breast, lung, GU and GI systems, bone, skin and brain. Mouse models of breast and lung cancer in literature revealed that CD24 attenuation in vivo leads to tumor inhibition and prolonged survival. To address the limited (~25%) overall response rate (ORR) of approved PD-1/PD-L1 antibodies for solid tumors, we developed IMM47, an IgG1 antibody that differentially targets phagocytosis and cytotoxicity onto CD24-expressing cancer cells. At doses between 3 mg/kg to 10mg/kg, IMM47 significantly reduced tumor volume in a MC38 mouse model of colon cancer. Mice treated with 10mg/kg IMM47 produced tumor-specific immune response that prevented growth of re-inoculation of colon cancer cells. Further mechanism of action studies showed that IMM47 selectively and differentially increased M1 spleen macrophages quantity to 7-10 folds higher in that induced by PBS control. In contrast, IMM47 only increased M2 spleen macrophages to less than 1.5 folds higher than induced by PBS control. Expression of MHC II in M1 macrophages was also increased in IMM47-treated mice, suggesting significant activation and antigen presentation by macrophages. Our data has also confirmed that IMM47 specifically binds to and induces ADCC (antibody-dependent cellular cytotoxicity),ADCP (antibody-dependent cellular phagocytosis), and CDC (complement-dependent cytotoxicity) against a variety of cancer cells. Taken together, our data show that targeting CD24 on tumor cells using our IMM47 antibody may serve as potent immunotherapy for multiple cancer indications. Citation Format: Wenzhi Tian, Song Li, Dianze Chen, Dandan Liu, Huiqin Guo, Chunmei Yang, Li Zhang, Wei Zhang, Xiaoping Tu, Liang Peng, Gui Zhao, Ruliang Zhang, Fan Zhang, Frank X. Gan. Preclinical development of a monoclonal antibody targeting CD24 as cancer immunotherapy. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6340.
Abstract 6306: Pharmacological deuteration of SCID mice using the water-isotopologue deuterium oxide (D2O) inhibits tumor growth in bioluminescent models of human malignant melanoma and pancreatic ductal adenocarcinoma
Authors: Jana Jandova, Jean-Philippe Galons, David L. Dettman, Georg T. Wondrak
Journal: Cancer Research (2023)

Abstract Since its initial discovery as a natural isotopologue of dihydrogen oxide (1H2O), extensive research has focused on the biophysical, biochemical, and pharmacological effects of deuterated water [2H2O (D2O, also referred to as ‘heavy water’)]. Here, using diverse panels of cultured human malignant melanoma and pancreatic ductal adenocarcinoma (PDAC) cells we have profiled (i) D2O-induced phenotypic anti-proliferative and apoptogenic effects, (ii) redox- and proteotoxicity-directed stress response gene expression, and (iii) phosphoprotein-signaling related to endoplasmic reticulum (ER) and MAP-kinase stress response pathways. Differential RT-qPCR array analysis revealed early modulation of stress response gene expression elicited by D2O (90%; ≤6 h) confirmed by independent RT-qPCR analysis. Immunoblot-analysis revealed rapid (&amp;lt; 6 h) onset of D2O-induced MAP-kinase signaling (p-JNK) together with ER stress response upregulation (p-eIF2α, ATF4, XBP1s, DDIT3/CHOP) attributable to deuteration-induced alteration of hydrogen bonding triggering proteotoxic stress. Next, we tested the chemotherapeutic efficacy of D2O-based drinking water supplementation in bioluminescent murine models of malignancy (A375-luc melanoma and BxPC-3-luc orthotopic PDAC xenografts in SCID mice). Time course of systemic deuteration (30% D2O in drinking water fed continuously for up to 21 days) was established using time-resolved whole-body proton magnetic resonance imaging (MRI) and isotope-ratio mass spectrometry (IR-MS)-based plasma (D/H)-analysis. In both models, D2O supplementation significantly suppressed tumor growth and metastasis with downregulated expression of PCNA/Ki67 while increasing tumor levels of DDIT3/CHOP, HO-1, and p-eIF2α. Taken together, these data demonstrate for the first time that pharmacological induction of systemic deuteration by oral administration of D2O, associated with induction of cellular ER stress, reduces tumor burden and metastasis in murine models of human malignant melanoma and PDAC. Citation Format: Jana Jandova, Jean-Philippe Galons, David L. Dettman, Georg T. Wondrak. Pharmacological deuteration of SCID mice using the water-isotopologue deuterium oxide (D2O) inhibits tumor growth in bioluminescent models of human malignant melanoma and pancreatic ductal adenocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6306.
Abstract 2216: Construction of a prognostic 6-gene signature for breast cancer based on multi-omics data
Authors: Zeyu Xing, Yuting Hong
Journal: Cancer Research (2023)

Abstract Breast cancer (BC) is a heterogeneous disease. Distinguishing BC patients with different prognosis can help to make clinical strategies. In our study, we tried to identify novel prognostic genetic biomarkers for BC by using multi-omics data and establish a risk score (RS) signature with genetic biomarkers which have high predictive value. A combined significance (pcombined) of each gene was calculated by Fisher’s method based on the p value of the difference examination of the respective index in RNA-seq, CNV, and DNA methylation data of corresponding genes from TCGA-BRCA dataset. Genes with a pcombined &amp;lt; 0.010 were subjected to univariate cox and Lasso regression to screen out hub genes, whereby a RS signature consisted of six genes, C15orf52, C1orf228, CEL, FUZ, PAK6, and SIRPG, was established. With the Kaplan-Meier (KM) method, the receiver operating characteristic curves (ROC), multivariate cox regression, Nomogram, and decision curve analysis (DCA), the predicted performance of the RS signature was assessed in TCGA-BRCA, GSE7390, and GSE20685. The predicted performance in TNBC patients was emphatically analyzed in TCGA-BRCA and GSE103091, while immune characteristics were also explored. Basing on the data from Genomics of Drug Sensitivity in Cancer (GDSC) database and related R package, we further examined the drug sensitivity of TNBC patients with different RS. With survival rates having significant differences in all KM analyses and most area under ROCs reaching 0.700, the RS signature could distinguish the prognosis of patients, even stratified by disease stages or subtypes. The RS also showed a stronger predictive ability than traditional clinical indicators, including age, tumor topology (T), regional lymph node (N), metastasis (M), and TNM stage. The down-regulated expressions of many immune checkpoints were observed in TNBC patients with higher RS, while the sensitivity of many antitumor drugs was reduced in those with higher RS, except for BI2536 (CAS No.: 755038-02-9), which demonstrated a smaller half maximal inhibitory concentration (which mean a higher drug sensitivity) in TNBC patients with higher RS. In conclusion, the six genes RS signature established based on multi-omics data exhibited well performance in predicting the prognosis of BC patients, regardless of disease stages or subtypes. Contributing to a more personalized treatment, the RS signature might benefit the outcome of BC patients. Citation Format: Zeyu Xing, Yuting Hong. Construction of a prognostic 6-gene signature for breast cancer based on multi-omics data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2216.
Abstract 5487: Synergy between FAK and PI3K inhibitors in cervical and pancreatic cancer cells
Authors: Chao-Cheng Chen, Suyang Wang, Jr-Ming Yang, Chuan-Hsiang Huang
Journal: Cancer Research (2023)

Abstract The Ras/PI3K/ERK signaling network is frequently mutated in many cancer types including cervical cancer and pancreatic cancer. Our previous study suggested that PI3K and FAK form a positive feedback loop to modulate ERK activation. We tested combined inhibition of FAK and PI3K on the growth of cervical and pancreatic cancer in vitro. We found that FAK and PI3K inhibitors synergistically inhibited the growth of some cervical cancer and pancreatic cancer cell lines. The synergy was due to both increased apoptosis and decreased cell proliferation. Molecularly, FAK inhibition caused downregulation of PI3K and ERK signaling in cervical cancer but not pancreatic cancer cells. Interestingly, PI3K inhibitors induced activation of several RTK including insulin R and IGF-1R in cervical cancer cells, as well as EGFR, Her2, Her3, Axl, and EphA2 in pancreatic cancer cells. Together, our results show the promise of combining FAK and PI3K inhibition for cervical cancer and pancreatic cancer treatment, but biomarkers for sensitivity to the combination are needed, and concomitant RTK inhibition may be required to combat potential resistance to the combination. Citation Format: Chao-Cheng Chen, Suyang Wang, Jr-Ming Yang, Chuan-Hsiang Huang. Synergy between FAK and PI3K inhibitors in cervical and pancreatic cancer cells. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5487.
Abstract 1380: Blocking autophagy ameliorates the severity of ConA induced autoimmune hepatitis in mice
Authors: Juan Wang, Cheng Qian, Chuanzhi Yangmeng, Li Fang, Ruiqing Yan
Journal: Cancer Research (2023)

Abstract Autoimmune hepatitis (AIH) recognized as a typical inflammation-triggered liver disease, which usually begins as acute hepatitis and ultimately develops to fibrosis, liver damage, loss of function of liver. It largely leads to the disease-related mortality and morbidity. However, the mechanism AIH remains unclear and the novel therapeutic reagents and methodology are urgently needed. In the present study, we established the ConA induced autoimmune hepatitis model in-house and evaluate autophagy and other immune signaling pathway on the participation of AIH. Our results bring the direction for the future direction of novel therapeutic reagents discovery. Citation Format: Juan Wang, Cheng Qian, Chuanzhi Yangmeng, Li Fang, Ruiqing Yan. Blocking autophagy ameliorates the severity of ConA induced autoimmune hepatitis in mice [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1380.
Abstract 5368: AI-enabled prediction of lung cancer specific hot spot gene alterations from histology images
Authors: Gowhar Shafi, Shiva Shivamurthy, Anand Ulle, Chongtham Cha Chinglemba, Sumit Haldar, Fauzul Moubeen, Mohan Uttarwar
Journal: Cancer Research (2023)

Abstract Background: The clinical intervention relies on molecular testing of primary biomarkers. We developed an AI enabled platform to predict NCCN guidelines recommended hot-spot genomic alterations from the image analysis using H&amp;E slide. Methods: AI engine was trained using clinically observed hot spot genomic alterations present in lung cancer patients as a ground truth based on histological FFPE whole-slide images. The H &amp; E stained histological images of the tumor having matching pathogenic mutations were downloaded from the TCGA database for the training and testing purpose. The program extracted histopathological features, followed by pattern mapping to predict genomics status based on the results of NGS testing from 480 samples. ResNet AI algorithm was trained to predict lung specific hot spot genomic alterations. An H &amp; E stained slide was imaged with a 40x objective lens to obtain a brightfield image as an input data. The input image was segmented into 65 x 103 tiles, each of 64 µm2 in size for an individual pathological class. 80% of the data set was used for training the engine while validation and blinded study was respectively performed on remaining 10% data. Results: Using single blinded clinical samples. AI model analyzed whole slides. Table 1 summarize parameters for clinically significant variants. Higher sensitivity and specificity was observed for variants encoding mutated cell surface proteins compared to variants encoding intracellular mutant targets when compared on similar training and testing parameters. Conclusions: AI-enabled prediction of hotspot genomic alterations resulted comparable to NGS with shortest TAT, cost and resources. It predicted actionable gene alterations with high positive and negative prediction values. Table 1. Gene Sample (n = 480) Evaluation parameters for tested samples Training Testing Sensitivity (%) Specificity (%) PPV (%) NPV (%) F1-score (%) Accuracy (%) KRAS 248 62 100 94 94 100 97 97 ALK 16 4 100 100 100 100 100 100 EGFR 72 18 88 100 100 90 94 94 MET 16 4 50 100 100 66 66 75 ROS 16 4 100 100 100 100 100 100 STK11 88 22 82 73 75 80 78 77 RET 24 6 50 100 100 60 50 67 BRAF 14 2 100 100 100 100 100 100 NTRK 92 24 78 56 64 71 70 67 ERBB2 12 4 50 50 50 50 50 50 Citation Format: Gowhar Shafi, Shiva Shivamurthy, Anand Ulle, Chongtham Cha Chinglemba, Sumit Haldar, Fauzul Moubeen, Mohan Uttarwar. AI-enabled prediction of lung cancer specific hot spot gene alterations from histology images. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5368.